Which types of data are appropriate for Pearson’s correlation coefficient?

Pearson’s correlation coefficient is specifically designed for variables measured on an interval/ratio scale.1

These variables are continuous in nature, meaning they represent data that can be measured on a continuous scale, such as height and weight. Pearson’s coefficient is used to quantify the strength of the linear relationship between two such variables. It is not appropriate for ordinal/rank scales—which are better suited for the Spearman rank-order correlation coefficient—or nominal/categorical scales, which typically require different statistical methods like the chi-square test.12